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Safety Cars in Strategy Simulation: What Changes Instantly
Race Analysis

Safety Cars in Strategy Simulation: What Changes Instantly

F1 strategy is often explained as tyre choice plus pace. In practice, it’s tyre choice plus timing, and nothing changes timing faster than a Safety Car. The moment race speed drops and gaps compress, the “cost” of a pit stop can fall sharply, and the value of track position can spike. That’s why the best way to think about Safety Cars in a calculator or simulator isn’t “who benefits?” but “what variables just changed, instantly?” This post breaks down those variables in a model-friendly way, so you can run scenarios in the Tyre Strategy Simulator and interpret the outputs without treating them like predictions.

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Undercut vs Overcut: How the Simulator Decides
Race Analysis

Undercut vs Overcut: How the Simulator Decides

An undercut vs overcut debate is usually framed as “who had the faster car” or “who called it first.” In reality, it’s a timing problem: you’re trading a known pit stop time loss for a probabilistic lap-time gain that depends on tyre warm-up, traffic, and how quickly the current stint is falling away. The most useful takeaway isn’t a single rule (“always undercut at X laps”)—it’s learning what the model is *actually* comparing, and how sensitive that comparison is to small input changes.

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Why “Optimal” Tyre Strategy Often Loses Races
Race Analysis

Why “Optimal” Tyre Strategy Often Loses Races

A good tyre strategy model is a calculator for conditional race time: if degradation behaves like this, if pit loss is that, if you rejoin in clean air, then Strategy A is faster than Strategy B. The problem is that real Grands Prix rarely respect a single clean set of assumptions. “Optimal” strategies are often the ones with the thinnest margins, and thin margins are exactly what chaos tends to destroy.

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